Vehicle-to-vehicle payment system for traffic prioritization in self-driving vehicles

ABSTRACT

A self-driving or autonomous vehicle has a traffic-prioritization processor to send or receive a payment to or from a central server to obtain a traffic prioritization for a route or to accept a traffic de-prioritization for the route. The central server receives and distributes payments to other vehicles traveling the route. The vehicle communicates with the central server to receive a plurality of levels of prioritization which range from a highest prioritization to a lowest prioritization, and the costs or payouts associated with each of the levels.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 16/283,767 entitled “VEHICLE-TO-VEHICLE PAYMENT SYSTEM FOR TRAFFIC PRIORITIZATION IN SELF-DRIVING VEHICLES” filed Feb. 23, 2019 which issued on May 25, 2021 as U.S. Pat. No. 11,017,665 which claims priority from U.S. Provisional Patent Application 62/634,904 filed Feb. 25, 2018, all of which are incorporated herein by reference.

TECHNICAL FIELD

The present invention relates generally to self-driving vehicles and, in particular, to traffic prioritization among autonomous or self-driving vehicles.

BACKGROUND

Autonomous or self-driving vehicles use sensors such as RADAR, LIDAR and/or cameras to provide signals to a processor or controller that generates and outputs steering, acceleration and braking signals to the vehicle. A Global Navigation Satellite System (GNSS) receiver such as a Global Positioning System (GPS) receiver is also used for navigation. As the self-driving vehicle drives autonomously toward a destination, the vehicle will encounter other self-driving vehicles. Self-driving vehicles in a given area of a road mutually sense each other's presence using various sensors for collision avoidance and may communicate, via vehicle-to-vehicle messaging protocols, with each other to avoid collisions.

There is a need for a system and method for giving priority, in certain circumstances, to one autonomous vehicle over another.

SUMMARY

In general, the present invention provides a self-driving vehicle system that includes a self-driving vehicle having a processor coupled to a transceiver to transmit and receive vehicle-to-vehicle (V2V) messages with one or more other autonomous vehicles. The V2V messages include a synchronization, or handshake, message to initiate a communication session with another vehicle. Once the two vehicles are communicating, the vehicle transmits an offer message to the other vehicle. The offer message includes an offer to pay or provide a financial compensation to the other vehicle in exchange for a priority of passage. The vehicle receives a reply message. The reply message may be an acceptance message or a rejection message. If the acceptance message is received, the vehicle transfers the payment to the other vehicle. Upon transfer of the payment, the vehicle automatically performs an adjustment to its routing to take advantage of the prioritization, e.g. to pass the second vehicle. In some cases, the second vehicle must move first to make room for the requesting vehicle, e.g. change lanes. The requesting may be done in response to user input or automatically (programmatically) based on a set of predetermined user settings.

The foregoing presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. This summary is not an exhaustive overview of the invention. It is not intended to identify essential, key or critical elements of the invention or to delineate the scope of the invention. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later. Other aspects of the invention are described below in relation to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features and advantages of the present technology will become apparent from the following detailed description, taken in combination with the appended drawings, in which:

FIG. 1 is a side view of an autonomous (“self-driving”) vehicle in accordance with an embodiment of the present invention.

FIG. 2 is a side view of two autonomous vehicles engaged in vehicle-to-vehicle (V2V) messaging to negotiate a payment to reprioritize their relative traffic positions.

FIG. 3 is a schematic depiction of a system for V2V messaging via a cellular data network.

FIG. 4 is a schematic depiction of a system for V2V payments for traffic reprioritization.

FIG. 5 is a data flow showing V2V messaging for transferring a payment from one autonomous vehicle to another to reprioritize their relative traffic positions.

FIG. 6 is another data flow showing V2V messaging for making a counteroffer to reprioritize their relative traffic positions.

FIG. 7 is a schematic depiction of parallel offer messages being transmitted from a single autonomous vehicle to two other autonomous vehicles.

FIG. 8 is a schematic depiction of serial offer messages being transmitted from a first autonomous vehicle to a second autonomous vehicle and then relayed from the second autonomous vehicle to a third autonomous vehicle.

FIG. 9 illustrates an example of a user interface of a navigation system that presents pricing and timing data to enable the user of the autonomous vehicle to select one of two routes based on both pricing and timing, wherein the pricing is computed by historical route pricing data for that time of day.

FIG. 10 is an example of a database showing prices for different prioritization levels for different road segments.

FIG. 11 is an example of a database showing prices for different prioritization levels for different road segments and further showing arrows indicating whether the prices are above normal market prices for that particular time and place.

FIG. 12 is an example of a database for bid-ask pricing for different prioritization levels for different road segments.

FIG. 13 is a schematic depiction of multiple vehicles entering an area and transmitting their route plans to a central server to enable pricing to be determined for that area.

FIG. 14 is a simplified example of a database showing the predicted locations of the vehicles at various times along each of the segments of the projected path.

FIG. 15 is a user interface of a navigation system showing an alert indicating that the estimated time of arrival will be later than originally predicted and providing the user to pay an amount to expedite the routing.

FIG. 16 is an example of a convoy of cars paying a second convoy of cars to pass them.

FIG. 17 is an example of a requesting car negotiating with an oncoming car to request that the oncoming car slow down to enable the requesting car to pass another vehicle by temporarily entering the lane of the oncoming car.

FIG. 18 is an example of an emergency vehicle, e.g. an ambulance, exchanging V2V messages with a vehicle.

FIG. 19 is an example of V2V messaging between two autonomous vehicles at or approaching respective stop signs.

FIG. 20 is an example of V2V messaging among four autonomous vehicles at or approaching a four-way stop.

FIG. 21 is an example of V2V messaging among four autonomous vehicles at or approaching an intersection with traffic lights in which the vehicles are further configured to send signals that interact with the timing of the traffic lights.

FIG. 22 is an example of V2V messaging between two autonomous vehicles that are approaching a common parking place.

FIG. 23 is an example of V2V messaging amongst multiple autonomous vehicles that are approaching a parking lot with limited spaces available.

FIG. 24 is an example of an autonomous vehicle using another vehicle as a wireless hotspot in exchange for traffic reprioritization.

FIG. 25 is an example of multiple users riding a first autonomous bus providing an aggregated request to multiple users riding a second autonomous bus.

FIG. 26 is an example of a truck delivery system in which three suppliers of goods automatically negotiate amongst each other, for example using artificial intelligence, to determine automatic payments to be made amongst the suppliers to prioritize the access of their respective autonomous trucks to a loading dock of a warehouse or store.

FIG. 27 is an example of a ship delivery system in which three suppliers of goods automatically negotiate amongst each other, for example using artificial intelligence, to determine automatic payments to be made amongst the suppliers to prioritize the access of their respective autonomous ships to a dockside crane or berth.

FIG. 28 is an example of a drone delivery system in which three suppliers of goods automatically negotiate amongst each other, for example using artificial intelligence, to determine automatic payments to be made amongst the suppliers to prioritize the access of their respective drones to a landing pad.

FIG. 29 is an example of user-configurable priority settings for different times of day that determine logic for how the vehicle automatically makes offers or accepts offers from other vehicles.

FIG. 30 is an example of a user-configurable multipliers for setting prices for various types of traffic manoeuvres.

It will be noted that throughout the appended drawings, like features are identified by like reference numerals.

DETAILED DESCRIPTION

Disclosed herein are various embodiments of a vehicle-to-vehicle payment system for traffic prioritization in self-driving (autonomous) vehicles. The vehicle, system and method that are disclosed in this specification enable one autonomous vehicle to communicate automatically or in response to user input with another autonomous vehicle to negotiate a traffic priority (i.e. preferential treatment) in exchange for a vehicle-to-vehicle payment or other valuable consideration. As such, one autonomous vehicle (AV) can pay another autonomous vehicle to let it pass, go first at a stop sign, take a parking place, etc. i.e. to grant it priority or precedence relative to the vehicle receiving the payment. In another implementation, an emergency vehicle (e.g. an ambulance, police car, fire truck, etc.) can request and obtain priority from nearby autonomous vehicles in traffic. Other embodiments and aspects are also disclosed.

For the purposes of this specification, the term “self-driving vehicle” is meant to encompass any vehicle such as a car, van, minivan, sports utility vehicle (SUV), crossover-type vehicle, bus, minibus, truck, tractor-trailer, semi-trailer, construction vehicle, work vehicle, tracked vehicle, semi-tracked vehicle, offroad vehicle, electric cart, dune buggy, or the like. Although the primary use of the technology is in relation to land-based vehicles, in particular on-road vehicles, in specific implementations that are disclosed herein, the term “vehicle” is meant to encompass unmanned aerial vehicles (drones) or ships, boats or other watercraft. The terms “autonomous” and “self-driving” in relation to “vehicle” are meant to encompass any vehicle having environment-detecting sensors and a processor, controller, computer, computing device or computer system for autonomously steering, accelerating and braking the vehicle, i.e. self-driving or driving autonomously, without a driver physically touching, interacting with or providing input to the steering wheel, accelerator pedal and brake pedal.

FIG. 1 depicts a self-driving car 10 as one exemplary implementation of a self-driving vehicle or autonomous vehicle (AV). The self-driving vehicle or autonomous vehicle 10 includes, in the illustrated embodiment, a vehicle chassis 12, a motor supported by the chassis for providing propulsive power for the vehicle, a braking system for braking (decelerating) the vehicle and a steering system for steering the vehicle via a steering mechanism which is usually connected to the front wheels. The motor may be an internal combustion engine, e.g. a gas engine or a diesel engine. The motor may alternatively be an electric motor. The motor may be a hybrid-electric powerplant. In a variant, the vehicle may have multiple electric motors for driving different wheels. In another variant, the motor may be a hydrogen fuel cell. The vehicle may include a powertrain to transfer power from the motor to the drive wheels. For some vehicles, the powertrain may include, in addition to the motor (engine), a transmission gearbox, a drive shaft, and a differential. For an electric vehicle implementation, the vehicle includes a rechargeable battery or plurality of rechargeable batteries.

The vehicle of FIG. 1 also includes a plurality of sensors i.e. environment-detecting sensors for collision avoidance. The sensors may include RADAR, LIDAR, cameras and ultrasonic rangefinders. The vehicle depicted by way of example in FIG. 1 includes a first sensor 14, a second sensor 16, a third sensor 18, and a fourth sensor 20. In the illustrated embodiment of FIG. 1 , the first sensor 14 is a RADAR sensor, the second sensor 16 is a LIDAR sensor, the third sensor 18 is a camera and the fourth sensor 20 is a side view camera. A fifth sensor 22 is in this illustrated embodiment a rear (backup) camera. Additional sensors may be provided on the vehicle 10, including additional camera, additional LIDAR and RADAR sensors. A different suite of sensors may be used in other variants.

The vehicle 10 may also be a mixed-mode human-drivable and self-drivable vehicle such as a self-driving car, truck, van, etc. that can be optionally driven directly by a human driver sitting in the driver's seat in which case the vehicle has two operating modes: (i) a conventional human driver mode with a human directly driving the vehicle using the steering wheel, brake pedal and accelerator as is conventionally done with non-autonomous vehicles; (ii) a self-driving mode in which the vehicle's processor or computing system drives autonomously without human input, whether a human is seated in the driver's seat or not.

The self-driving vehicle 10 of FIG. 1 further includes a self-driving processor 100 or computing device configured to receive analog or digital signals (data) from the sensors and to generate steering, acceleration and braking control signals for controlling the steering system, the motor and the braking system of the vehicle. The processor 100 may generate a steering control signal, an acceleration control signal and a braking control signal based on the signals received from the sensors. The processor 100 may also generate other control signals for other subsystems and equipment on the vehicle, e.g. a turn indicator light control signal, a horn control signal, a headlight control signal, a transmission selector signal, an ignition shutoff signal, an ignition start-up signal, a door lock signal, a door unlock signal, a windshield defroster signal, a windshield wiper activation signal, a wiper fluid squirt signal, climate control signal, headlight activation signal, to name but a few.

The vehicle 10 depicted in FIG. 1 also includes a traffic-prioritization processor 200 which may be integrated with the self-driving processor or connected thereto. The processors 100, 200 may be, include, or be part of, any microprocessor, computer, computing device, or microcontroller. In the illustrated embodiment, the self-driving processor 100 and the traffic-prioritization processor 200 are shown as having being implemented as an integrated computing device that has a shared microprocessor 210 and memory 220. Alternatively, the processors 100, 200 may be discrete processors that are communicatively connected or networked together to share data and computational loads. Alternatively, the processors 100, 200 may be separate cores of the same processor, or discrete processors of the same computing device. As will be appreciated, in a variant, there may be multiple processors or computers working together to perform the tasks of the processors 100, 200, e.g. networked together via data buses, communication cables, or wireless links to share computational loads or to perform different tasks.

In the embodiment depicted in FIG. 1 , the self-driving processor 100 and the traffic prioritization processor 200 are implemented as a vehicle computing device that has a single microprocessor 210 operatively coupled to a memory 220, e.g. a flash memory and/or random access memory (RAM). The memory may store system data, configuration files and user-related data, rules, parameters and settings. There may be multiple memory devices in the vehicle. In a variant, data may be stored in a cloud-based memory accessible by the vehicle. The vehicle computing device may be part of a vehicle computer system that manages other vehicle functions like engine control, navigation, entertainment, etc.

The self-driving vehicle 10 depicted by way of example in FIG. 1 further includes a data transceiver 230, e.g. a cellular data transceiver, a satellite transceiver or any other radiofrequency data transceiver. The data transceiver may be any suitable wireless data transceiver for transmitting and receiving data wirelessly. In one main embodiment, the data transceiver 230 is a cellular data transceiver. The data transceiver 220 is configured to wirelessly communicate data from the vehicle to the remote control device by attaching communicatively to a base station transceiver 222. Data is transmitted and received over a cellular wireless network using cellular communication protocols and standards for packet data transfer such as GSM, CDMA, GPRS, EDGE, UMTS, LTE, etc. The vehicle may include a Subscriber Identity Module (SIM) card for GSM-type communications or a Re-Usable Identification Module (RUIM) card for CDMA-type communications. The data transceiver may optionally include separate voice and data channels. From the base station transceiver 222 the data is communicated in the illustrated embodiment via the internet 250 to another vehicle or a server or other user equipment, as will be explained below.

The vehicle 10 may also include a Wi-Fi® transceiver 240 and a Bluetooth® transceiver for short-range data communication with other vehicles as will be elaborated below.

The vehicle 10 may also exchange V2V messages using IEEE 802.11p Dedicated Short-Range Communications (DSRC) in the 5.9 GHz band used, or to be used, by intelligent transportation systems (ITS). The DSRC messages are half duplex messages in the 5.850-5.925 GHz range and are short-range (approximately 300 m) and have a high data rate of 6-27 Mbps.

The vehicle 10 may optionally include one or more data communication ports or sockets for wired connections, e.g. USB, HDMI, FireWire (IEEE 1394), etc. or ports or sockets for receiving non-volatile memory cards, e.g. SD (Secure Digital) card, miniSD card or microSD card. These physical data connections may be used to load data onto the memory 220 or to copy data from the memory 220. For example, the data communication ports may be used to upgrade software, to obtain diagnostics for servicing and maintenance, or to upload configuration data to the memory to configure the vehicle for different types of behaviours.

The self-driving vehicle 10 depicted by way of example in FIG. 1 further includes a Global Navigation Satellite System (GNSS) receiver 260 for receiving satellite signals and for determining a current location of the self-driving vehicle. The GNSS receiver may be a Global Positioning System (GPS) receiver that decodes satellite signals transmitted by orbiting GNSS satellites. The GNSS (or GPS) receiver may be part of the vehicle navigation system. The GNSS or GPS receiver (e.g. in the form of a chip or chipset) receives GNSS/GPS radio signals transmitted from one or more orbiting GNSS/GPS satellites. References herein to “GPS” are meant to include Assisted GPS and Aided GPS. Although the present disclosure refers expressly to the “Global Positioning System”, it should be understood that this term and its abbreviation “GPS” are being used expansively to include any satellite-based navigation-signal broadcast system, and would therefore include other systems used around the world including the Beidou (COMPASS) system being developed by China, the multi-national Galileo system being developed by the European Union, in collaboration with China, Israel, India, Morocco, Saudi Arabia and South Korea, Russia's GLONASS system, India's proposed Regional Navigational Satellite System (IRNSS), and Japan's proposed QZSS regional system.

As depicted in FIG. 1 , in the self-driving (autonomous) vehicle 10, the processor 200 is communicatively coupled to one or more transceivers 230, 240, 250 to transmit and receive vehicle-to-vehicle (V2V) messages to and from one or more other autonomous vehicles in the vicinity of the self-driving vehicle. The messages may be transmitted wirelessly by cellular, Wi-Fi®, Bluetooth®, IEEE 802.11p as a 5.9 GHz DSRC message or any other short-range wireless technology or protocol. The V2V messages in one embodiment include an initial synchronization message, or handshake message, to initiate a communication session with another vehicle based on prior knowledge of the other vehicle's network address or other identifier. The synchronization/handshake message may be a datagram having data bits that are arranged in a recognizable sequence. Alternatively, the V2V messages may be broadcast with a header, pilot signal or preamble data to be recognizable by other vehicles listening within range in the vicinity of the broadcasting vehicle. The V2V messages may be formatted with a preamble field, signal field and a payload component containing the message data according to IEEE 802.11p. The preamble field of IEEE 802.11p has twelve training symbols that describe the frequency channel behaviour and synchronization of the reception. According to the standard, this includes ten Short Training Symbols (STS) and two Long Training Symbols (LTS). Seven of the ten STS are short OFDM symbols for signal detection, automatic gain control (AGC) and diversity selection. Three of these are for coarse frequency offset and timing synchronization. Also, these permit the estimation of the subcarrier frequency and channel estimation. The signal field specifies rate and length information. It has one OFDM symbol assigned to all 52 subcarriers. This symbol is BPSK modulated at 6 Mbps and is encoded at a half rate. The signal field data is interleaved and mapped, and has pilots inserted in subcarriers −21, −7, 7 and 21. The signal field has 24 bits divided into five sub fields, the RATE, RESERVED, LENGTH, PARAITY and TAIL. The RATE field is the first four bits which convey information about the type of modulation and the coding rate used in the rest of the data packet. Other data formats or message formats may be used in other embodiments.

As depicted in FIG. 2 , a first autonomous vehicle 10 and a second autonomous vehicle 10 a communicate by exchanging V2V messages 11 using a short-range wireless connection protocol, e.g. Wi-Fi, Bluetooth or IEEE 802.11p. The messages may be transmitted via an RF signal carrying a bit stream of digital data. The first and second vehicles 10, 10 a communicate automatically or in response to user input or user command that trigger the messaging. The V2V messaging enables the two vehicles to automatically negotiate a price or other valuable consideration for giving preferential traffic treatment to one of the two vehicles to the detriment of the other, e.g. letting one vehicle pass the other. In one example, the first AV 10 may pay the second AV 10 a to pass. In another example, the first AV 10 may pay the second AV 10 a to yield at an intersection, on-ramp, roundabout, parking lot, or in any other situation when the vehicles meet and one of the two can be given precedence over the other.

The V2V messaging may begin with a synchronization message broadcast to vehicles in the vicinity. In one embodiment, the vehicle may use a machine vision algorithm recognize a license plate number and then to look up the license plate in a database, then to transmit the request to a specific number, address, etc. of the vehicle. For example, if the vehicle approach behind a vehicle and wishes to pass the vehicle, the vehicle obtains a camera image of the license plate, looks up the number/address associated with the license plate, and then sends the synchronization message to the vehicle ahead. In another embodiment, vehicles driving in proximity are continually forming and reforming ad hoc mobile wireless networks using a short-range wireless communications technology. The receiving vehicle may accept or reject the handshake message. If the handshake is accepted, the vehicles are synchronized and may then communicate data representing the V2V messages.

Once the two vehicles are communicating, the first vehicle 10 transmits an offer message as a datagram or bitstream to the second vehicle 10 a. The offer message or offer datagram may include data bits identifying the sending/offering vehicle, data bits indicating what the request is (allow the requesting vehicle to pass, speed up for a single lane roadway, etc.). The offering datagram may include data bits providing an offer of payment or other financial incentive (e-coupon, sharing wireless data, sharing battery charge for vehicles that charge while driving, or other valuable goods or services). The offer message includes an offer to pay or provide a financial compensation to the other vehicle in exchange for a priority of passage or some other traffic-related adjustment or reprioritization. For the purpose of this specification, the terms prioritization and reprioritization are used generally synonymously to indicate that the vehicle making the payment obtains an advantage or preferential treatment relative to the vehicle receiving the payment. The requesting vehicle 10 (i.e. the first AV) receives a reply message from the receiving vehicle 10 a (i.e. the second AV). The reply message may be an acceptance message or a rejection message. Formulation of the reply message may be done automatically or in response to user input. For automatic replies, the receiving vehicle is programmed with a set of rules, parameters or settings that determine how incoming offers are to be processed. For example, a request to pass might require more than $2 dollars to be accepted. Any offer below $2 is automatically rejected. Any offer of $2 or higher is automatically accepted. The receiving vehicle would thus have a rule defining a monetary threshold to automatically accept an offer from a requesting vehicle.

If the acceptance message is received, the first autonomous vehicle 10 transfers the payment to the other (second) vehicle 10 a. Upon transfer of the payment, the second vehicle 10 a automatically performs an adjustment to its routing, speed, position or behaviour to enable the first vehicle 10 to take advantage of the prioritization, e.g. enable the first vehicle to pass the second vehicle. In some cases, the second vehicle 10 a must move first to make room for the requesting vehicle 10, e.g. change lanes. The transmission of the request message may be done in response to user input or automatically (programmatically) based on a set of predetermined user settings. For example, the first AV may be programmed to travel as fast as possible up the maximum speed limit. If the second AV is traveling less than the first AV is attempting the travel, then the first AV will automatically transmit a V2V message requesting that to pass the second AV. The V2V message requesting to pass contains data bits representing a price or payment that the user or occupant(s) of the first AV is or are willing to pay to pass the second AV. The second AV is programmed with its own rules to process the request and to determine whether the offer is acceptable. If so, the second AV replies to the first AV with an acceptance message.

This V2V payment-based traffic reprioritization system and method enables users (i.e. riders, passengers, occupants) of autonomous vehicles to pay to have precedence or priority of passage while others are able to receive payments to yield or grant precedence to others who may in a rush. This V2V payment-based traffic reprioritization system and method may be used in various traffic scenarios and situations, e.g. at stop signs, traffic lights, roundabouts or other traffic situations where two vehicles compete for priority or precedence. A commuter riding in one AV who is not in a rush may thus be able to make money during his or her commute by letting commuters in other vehicles pass or take precedence. The commuter who finds himself or herself in a rush may thus pay to expedite his or her commute.

The V2V payment-based traffic reprioritization system and method enables peer-to-peer negotiation of pricing for the traffic prioritization. The logic, parameters or rules set by each user are executed by respective processors 200 in each vehicle to automatically negotiate a mutually acceptance price for the reprioritization. The prioritization and pricing rules may be time-based rules and/or date-based rules and/or location-based rules, so that the prioritization and pricing rules change based on when and where the autonomous vehicle is operating. For example, the commuter on the weekend might not care about arriving on time and thus be willing to yield to other vehicles in order to earn some extra money. However, on Monday morning, when traveling to work, the commuter in the autonomous vehicle may not be willing to delay his route.

The V2V payment-based traffic reprioritization system and method may be refined to permit counteroffers to be made. For example, the processor 200 of the receiving vehicle may be configured to generate a counteroffer if the offer is not acceptable in terms of inconvenience and/or price. In the counteroffer paradigm, the autonomous vehicle receiving the initial offer is configured to reply with a counteroffer back to the requesting vehicle. Upon receipt of the counteroffer, the requesting vehicle can then accept or reject the counteroffer. Further negotiations, e.g. counter-counteroffers, counter-counter-counteroffers, and so on, can be made in other variants.

To prevent some commuters from trolling the roads by intentionally slowing down their vehicles to frustrate other commuters, the system may have a minimum threshold below which the payment system is automatically deactivated. For example, a given segment of road may have a maximum and a minimum speed within which the AV must be traveling in order to be eligible to receive a payment.

The payment may be made in a national currency, e.g. U.S. dollars, Euros, Canadian dollars, Australian dollars, Japanese Yen, Mexican Pesos, British Pounds, etc. depending on the location of the first and second vehicles at the time the transaction is completed. Payment may be made in bitcoin or other cryptocurrency. Payment may be made with another form of valuable consideration such as e-coupons for gas or battery recharging, food, or other services. Payment may be made in loyalty points redeemable for goods and services (air miles, credit card points), for vouchers for meals at service stations along the road, credits for entertainment (e.g. iTunes), etc.

In one embodiment, the first and second autonomous vehicles 10, 10 a can share a cellular wireless connection (allowing one vehicle to piggyback or use the other's cellular or satellite connection) in which case one vehicle can offer to provide cellular or satellite bandwidth to the other vehicle as payment for the traffic reprioritization.

In another embodiment, the exchange can simply be redeemable for reciprocal privileges at a later date. For example, a vehicle who cedes the way to another may accumulate redeemable points to use to request privileges from that or other vehicles when needed or desired. Thus, the system and method may utilize its own internal currency to create credits and debits among users or subscribers. The payment in one embodiment comprises a transfer to the second vehicle of redeemable points that are stored in a database and are redeemable for a subsequent traffic prioritization in favor of the second vehicle.

Autonomous vehicles may automatically or programmatically negotiate with other nearby autonomous vehicles to reprioritize their relative traffic positions, priority or precedence, which is herein referred to generally as a traffic prioritization or reprioritization. One example of a simply reprioritization is a first vehicle passing a second vehicle. As another example, the first and second vehicles can negotiate who should yield at an intersection, at a stop sign, or who should get priority as vehicles merge into a single lane. The first and second vehicles can negotiate automatically between each other, sending V2V messages back and forth, to determine who gets to go first when the vehicles meet at a stop sign, or who gets priority when two vehicles arrive simultaneously at a parking spot or at a drive-through entrance, for example.

In one implementations, a local government authority maintaining the roadways (e.g. a municipality, city, state, nation, etc.) may tax the V2V payments as a means of raising funds to maintain the road infrastructure. In another implementation, some of the payments may be made to a government authority rather to other vehicles. Thus, two autonomous vehicles entering a parking lot may bid dynamically for the parking space. Thus, if there is only a limited number of parking spots, the vehicles can bid for the parking spaces, with the prices thus fluctuating depending on supply and demand. In a hybrid implementation, the vehicle offers both the governmental authority and the other vehicle a payment to get priority.

FIG. 3 is a schematic depiction of a system and method for V2V messaging via a cellular data network. Instead of a direct short-range wireless connection between the vehicles, as was shown in FIG. 2 , the system of FIG. 3 uses a cellular data connection to exchange messages between the vehicles. The first vehicle has a first device identifier and the second vehicle has a second identifier, which may be any system or protocol akin to GSM, LTE or 5G handheld mobile devices that enable data messages to be communicated over the cellular network.

FIG. 4 is a schematic depiction of a system and method for V2V payments for traffic reprioritization between two vehicles having direct wireless connectivity. In this example, the first autonomous vehicle 10 exchanged V2V messages 11 with the second autonomous vehicle 10 a to negotiate a payment for a traffic reprioritization. Assuming the transaction proceeds because both parties agree to the price, the first vehicle 10 communicates via a base station transceiver 222 of a wireless network via the internet (or other data network) with a first bank server or payment processing server 300 associated with a first user of the first AV 10. The AV 10 transfers a payment electronically (via the internet 250) to the second bank server or payment processing server 302 which then notifies the second AV 10 a of the transfer via a wireless communication transmitted by the base station transceiver 222 (or by a different base station transceiver if the second AV 10 a uses a different wireless carrier).

FIG. 5 is a messaging data flow showing V2V messaging for transferring a payment from one autonomous vehicle to another to reprioritize their relative traffic positions. In FIG. 5 , the first AV 10 is associated with a first payment server 300 whereas the second AV 10 a is associated with a second payment server 302. Being associated with a payment server means, in most embodiments of the invention, that the user/owner/operator/commuter/passenger/occupant of the AV has a bank account or financial account with a bank, payment processing facility, financial institution, credit card company or equivalent and is thus able to pre-program the AV to perform automatic financial transactions (make payments or receive payments) using money in the bank account or financial account.

As shown by way of example in FIG. 5 , the requesting vehicle (first AV) requests a connection or session with the second AV. The second AV accepts (or rejects) the request to create a connection or session. This is known herein as the handshake request. The first AV checks that it has funds to make an offer by communicating with the first payment server. The first payment server confirms (or not) that sufficient funds are available. Upon receipt of this confirmation, the first AV automatically transmits the offer message to the second AV. On receipt of the offer message, the second AV applies its acceptance rules to the offer and automatically accepts or rejects the offer from the first AV but does not communicate the acceptance to the first AV until it has verified that the funds are immediately available for transfer from the first AV. If the offer is accepted by the second AV, the second AV asks its own payment server (payment server 2) to verify that the funds are available from the first AV, i.e. that the first AV can afford to pay the offered amount. The second payment server 302 sends a fund verification request to the first payment server 300. The second payment server 302 receives a fund verification message from the first payment server 300 to confirm that the funds are immediately available to be transferred. The second payment server 302 then sends a fund verification confirmation to the second AV to notify the second AV that the funds are available. Once this confirmation is received, the second AV 10 a transmits the acceptance message to the first AV 10. The first AV 10 replies with an acknowledgement message. The first AV 10 then sends a fund transfer request to the first payment server 300. In response to receiving the fund transfer request, the first payment server 300 electronically transfers the funds to the second payment server 302 into the account associated with the second AV. The second payment server 302 then sends a fund receipt notification to the second AV. The second AV, upon receipt of the confirmation that the funds have been transferred, automatically initiates the traffic manoeuvre to give priority or precedence to the first AV.

FIG. 6 is another data flow showing V2V messaging for making a counteroffer to reprioritize their relative traffic positions. This message data flow is similar to the one presented in FIG. 5 except that the second AV replies with a counteroffer. The reply message containing the counteroffer is processed by rules and logic stored in the processor 200 of the first AV. If the counteroffer is accepted by the first AV, the first AV transmits a counteroffer acceptance message back to the second AV. It will be appreciated that the negotiation could involve multiple messages back and forth. In some cases, the offer message has an expiry time or becomes void if the second AV moves beyond a predetermined amount from its current position relative to the first AV.

FIG. 7 is a schematic depiction of parallel offer messages being transmitted (e.g. broadcast) from a single autonomous vehicle to two other autonomous vehicles. In this example, the first AV 10 broadcasts or multicasts request messages to a second AV 10 a and a third AV 10 b. In this case, the first AV may be configured to transact with either or both of the second AV and the third AV. As an example, consider a scenario in which the second AV and the third AV are traveling side by side in two adjacent lanes preventing the first AV from passing. The first AV may broadcast a request to both the second AV and the third AV to offer a payment in exchange for letting the first AV pass one of the two vehicles. If the second AV replies before the third AV, the first AV performs the transaction with the second AV only. In this case, the offer is a conditional offer. The V2V offer message may contain bits in a data field indicating that the offer is conditional, e.g. first to reply, time-limited, location-limited, etc.

FIG. 8 is a schematic depiction of serial offer messages being transmitted from a first autonomous vehicle (AV) 10 to a second autonomous vehicle (AV) 10 a and then relayed from the second autonomous vehicle (AV) 10 a to a third autonomous vehicle (AV) 10 b. In one embodiment, the second AV 10 a replies to the request made by the first AV 10 to indicate that it alone cannot take the requested action because of the presence of another vehicle, in this example the third AV 10 b. The second AV 10 a relays the request from the first AV to the third AV. The third AV replies with an acceptance (or a rejection) which the second AV transmits back to the first AV. Assuming the third AV accepts the offer from the first AV, the second AV transmits its own acceptance to the first AV. The first AV then makes a payment to both the second AV and the third AV, which may be the same amount or different amounts. The second and third AV then cede the way, or give precedence, to the first AV. In another embodiment, the first AV makes conditional offers to both the second AV and third AV which is ahead of the second AV. The offer message contains bits in a data field indicating that the offer is conditional on both the second AV and the third AV accepting; otherwise, the offer is null and void. Provided both the second AV and the third AV accept the offers, the first AV transfers payments to the second AV and to the third AV. The example presented in FIG. 8 is a simple three vehicle scenario. However, it will be appreciated that the concept of conditional offers may be extrapolated to a larger number of vehicles.

In another embodiment, the acceptance by the second vehicle of an offer from the first vehicle may be conditional on the acceptance of the second vehicle's own offer to a third vehicle. In such a case, the acceptance message communicated back to the first vehicle indicates that the acceptance is conditional pending acceptance of another offer made by the second vehicle to the third vehicle. The first vehicle may apply its own time-based rules or location-based rules to withdraw or nullify the offer after a predetermined time has elapsed or if the vehicle's relative positioning has changed more than a predetermined amount. An offer withdrawal message (or offer cancellation message) may be communicated automatically from the first vehicle to the second vehicle.

FIG. 9 illustrates an example of a user interface 400 of a navigation system that is integrated or communicatively coupled with the traffic prioritization processor 200 of the autonomous vehicle. The user interface 400 may displayed on a touch-sensitive display screen in the vehicle. The processor presents pricing and timing data via the user interface 400 to enable the user of the autonomous vehicle to select one of two routes based on both pricing and timing. In one embodiment, the pricing is computed based on historical route pricing data for that time of day. A first route 410 and a second route 420 are shown graphically on a map displayed on the user interface 400. The user interface 400 presents a first user-selectable interface element 430 which presents an estimated price and travel time for the first route ($15 and 22 minutes). The user interface 400 presents a second user-selectable interface element 440 which presents an estimated price and travel time for the second route ($19 and 18 minutes). In this example, if the user is in a rush, he can choose the second route by touching (selecting) the second user-selectable interface element 430. The second route costs $4 more but saves 4 minutes of travel time. All prices and times in this specification and drawings are solely presented as examples and are not meant to limit the scope of the invention.

In the above implementations, the vehicles perform V2V messaging individually between vehicles to negotiate discrete traffic reprioritization events. In another paradigm, a central server, server cluster, server farm or cloud-based manager can act as a central intermediary for all offers and acceptances for vehicles traveling through a given geographical area.

FIG. 10 is an example of a database showing prices for different prioritization levels for different road segments for a geographical area at a particular time of day and day of the week. FIG. 10 shows as an example how the pricing varies for different prioritization levels for different road segments. Instead of peer-to-peer negotiations for each traffic event, this aggregated pricing model may be used in a centrally regulated paradigm in which a central authority server acts as an intermediary for all offers and requests to simplify messaging. The database of FIG. 10 contains specific pricing for a zone or area, e.g. Boca Raton, Fla. and for a specific day, e.g. March 12 at 5 p.m. Five levels of prioritization are provided in this example: highest priority, high priority, normal, low priority and lowest priority. Five roadways are presented in this exemplary database: 1-95 North, 1-95 South, Glades Road, Palmetto Park Road, and Yamato Road. The number of roads and levels of priority are presented solely as an example. For example, a vehicle traveling a predetermined segment along 1-95 North in the Boca Raton area whose passenger wishes to have the highest priority would pay $11.07. High priority would cost $6.95. No reprioritization (i.e. not participating) would cost nothing (zero dollars). Selecting low priority would mean the user would receive $6.95. Selecting the lowest priority would mean the user would receive $11.07. The pricing varies for each of the different roadways as shown. The pricing may dynamically fluctuate in time for a given roadway, road segment, or location based on supply and demand. The aggregate pricing model simplifies the transactions for the autonomous vehicles. The vehicle may display the prices for the user to select a priority level at the beginning of a drive, when entering the vehicle or when programming a route in a navigation system of the vehicle, on demand in response to a user request, when the prices have changed, or based on any other trigger, condition or event.

FIG. 11 shows a variant of the database of FIG. 10 further showing arrows indicating whether the prices are above normal market prices for that particular time and place. The arrows provide pricing to enable the user to make an informed decision.

FIG. 12 is an example of a database for bid-ask pricing for different prioritization levels for different road segments for use in a centrally regulated paradigm in which a central authority server acts as an intermediary, broker or clearinghouse for all offers and requests to simplify messaging. The central authority server receives all payments from prioritized vehicles and distributes the money to the de-prioritized vehicles. The bid is the price being offered for the prioritization. The ask is the price the receiving vehicle is asking to grant the prioritization. In this example, analogous to the example presented in FIG. 10 and FIG. 11 , the bid-ask database contains specific pricing for a zone or area, e.g. Boca Raton, Fla. and for a specific day, e.g. March 12 at 5 p.m. Five levels of prioritization are provided in this example: highest priority, high priority, normal, low priority and lowest priority. Five roadways are presented in this exemplary database: 1-95 North, 1-95 South, Glades Road, Palmetto Park Road, and Yamato Road. The number of roads and levels of priority are presented solely as an example. In this bid-ask pricing model, a vehicle traveling a predetermined segment along 1-95 North in the Boca Raton area can view what it would cost to expedite his travel by requesting high priority or highest priority. Conversely, the user can see how much it would pay to reduce to low priority or lowest priority. Note that there is a pricing asymmetry between the bid and the ask due to differential amounts of users wishing to either speed up their travel or to make money by ceding precedence, i.e. a disequilibrium in the supply and demand. During rush hour, for example, there may be more demand for express routing than on the weekend, meaning that more people are willing to pay than to be paid. Over time, this causes the price to rise. When the number of users wishing to speed up equals the number of users wishing to slow down for a given segment at a given time, the bid and ask converge to the same price point. Thus, in this example, the price to be granted the highest priority along 1-95 North is $10.79. Conversely, along the same segment of roadway, the central authority server would pay the user of the AV $12.05 to accept to be given the lowest priority. To request high priority, the bid price is $7.28 whereas the ask price is $6.92. This means that, at that particular time and place, it would cost $7.28 to be granted high priority whereas it would pay the user $6.92 to accept low priority. The bid-ask pricing road segments may be displayed on a user interface in the autonomous vehicle for selection by the user of the autonomous vehicle.

FIG. 13 is a schematic depiction of multiple autonomous vehicles entering an area via various routes or entry points and transmitting, upon entry into the area or beforehand, their respective route plans to a central server 500 to enable pricing to be determined for that area. The pricing is based in this embodiment on a comparison of all of the potential vehicle-to-vehicle interactions (potential inference between vehicles competing for traffic precedence). V2V interactions occur when two or more vehicles travel close to each other, i.e. within a predetermined distance threshold such that at least one vehicle's progress is at least partially or potentially hindered, inhibited or retarded by another vehicle. Summing each of these V2V interactions establishes congestion indices for each segment of each route, and enables the computation of an estimated delay time and thus of an estimated time of arrival for a given route to a destination. Based on the projected congestion indices, the central server can compute and broadcast travel times with and without prioritization, or with different levels of prioritization, along with respective costs or payouts for each level of prioritization. A cost in this context means an amount the vehicle pays to get higher precedence (lower level prioritization in traffic). A payout in this context means an amount the vehicle receives to accept a lower precedence (lower level prioritization in traffic).

FIG. 14 is a simplified example of a database showing the predicted locations of the vehicles at various times along each of the road segments of the projected path. The central server 500 generates a database, data structure or table that predicts the locations of autonomous vehicles as they traverse an area of interest. The central server 500 predicts, for every vehicle in the area, which segment each vehicle will be traveling along during which timeslot. For example, consider the predicted progress of vehicle 01 as the travels along road segments 1 to 6. During the first timeslot (12:00-12:01 p.m.), vehicle 01 is traveling along road segment 1. As vehicle 01 is traveling along road segment 1, vehicles 02, 03, 04, and 05 are also simultaneously traveling along that same segment of road. The central server 500 can thus estimate the likely congestion based on the number of vehicles. The central server 500 can then determine pricing amongst those vehicles based on their stated preferences (high priority, low priority, etc.) and can furthermore broker payments amongst the vehicles. During the second timeslot (12:01-12:02 p.m.), vehicle 02 is traveling along road segment 2. Only vehicle 02 is nearby vehicle 01 at that time along road segment 2. During the third timeslot (12:02-12:03 p.m.), vehicle 01 is traveling along road segment 3. In addition to vehicle 02, vehicle 08 is also nearby as vehicle 01 travels along road segment 3. During the fourth timeslot (12:03-12:04 p.m.), vehicle 01 is traveling along road segment 4 along with vehicles 02 and 10. During the same fourth timeslot (12:03-12:04 p.m.), vehicle 01 travels along road segments 5 and 6, encountering vehicles 03, 08, and 09 along road segment 5 and vehicles 04, 13, 14 and 20 along road segment 6.

FIG. 15 is a user interface 400 of a navigation system of the autonomous vehicle showing an alert 450 indicating that the estimated time of arrival will be later than originally predicted and providing the user with an option to pay an amount to expedite the routing. The amount may be calculated based on the predicted amount of V2V interactions and the expected cost, based on historical data, to be granted priority along the route. The user interface includes a pay button 460, an ignore button 470 and a virtual button to request other routing options 480. The other routing options may present detours and alternate routes with respective travel times and associated costs.

FIG. 16 is an example of a first convoy 600 of autonomous vehicles paying a second convoy 610 of autonomous vehicles to pass the first convoy 600. Although the reprioritization in this example is passing, the traffic reprioritization for which the first convoys pays the second convoy, may be any other action such as yielding the way, giving precedence at an intersection, etc. The convoys may be motorcades or any other groups of vehicles that are following a leader en route to a common destination. The group of vehicles may be, for example, communicatively linked to each other or to the lead vehicle. In this example, a first lead vehicle 602 of the first convoy 600 communicates with a second lead vehicle 612 of the second convoy 610 to negotiate the payment for the privilege of passing. In this example, all of the vehicles behind the first lead vehicle in the first convoy are automatically following the first lead vehicle whereas all of the cars behind the second lead vehicle in the second convoy are also automatically following the second lead vehicle.

FIG. 17 is an example of a requesting car 10 negotiating via V2V messages 11 with an oncoming car 10 a to request that the oncoming car 10 a slow down to enable the requesting car 10 to pass another vehicle directly ahead of it by temporarily entering the lane of the oncoming car 10 a. In a variant, the requesting car 10 also notifies and/or negotiates with the vehicle directly ahead of it to ensure that this vehicle does not accelerate, change lanes or perform some action that would affect the safe passing by the requesting car.

FIG. 18 is an example of an emergency vehicle 10, e.g. an ambulance, exchanging V2V messages 11 with another vehicle 10 a that is hampering the progress of the emergency vehicle. In a first paradigm, the emergency vehicle makes the request without offering any payment because the vehicle is an emergency vehicle. The autonomous vehicle 10 a receiving the request from the emergency vehicle is programmed to automatically cede the way to any emergency vehicle (ambulance, fire truck, police car, etc.) without requiring any payment. A special code may be transmitted wirelessly by emergency vehicles, e.g. when their sirens are activated or in other circumstances, that is automatically recognizable by autonomous vehicles. In a second paradigm, the emergency vehicle makes a small nominal payment that is paid for by the state or, for example, by the ambulance company.

FIG. 19 is an example of V2V messaging between two autonomous vehicles at, or approaching, respective stop signs at an intersection. As depicted in FIG. 19 , a requesting vehicle 10 initiates V2V messaging 11 with a receiving vehicle 10 a to request priority or precedence at the intersection. Although the rules of the road in many jurisdictions dictate that the vehicle must give precedence to the vehicle to the right when arriving simultaneously at an intersection, the requesting vehicle 10 may offer to the receiving vehicle 10 a a payment to be granted precedence at the intersection. In one implementation, the vehicle 10 detects the arrival of the other vehicle 10 a and predicts that the two vehicles will arrive substantially simultaneously at the intersection. The vehicle checks whether the user has specified a priority level for events such as meeting at intersections. If the user has prescribed a precedence-seeking behaviour for the traffic event (e.g. meeting at an intersection), the requesting vehicle 10 then transmits a V2V message to the receiving vehicle 10 a requesting that it be given precedence and offering a payment to the receiving vehicle for this preferential treatment.

FIG. 20 is an example of V2V messaging among four autonomous vehicles 10, 10 a, 10 b, 10 c at, or approaching, a four-way stop. In this scenario, V2V messages 11 may be exchanged between each pair or combination of vehicles. For example, a first vehicle 10 communicates with a second vehicle 10 a, a third vehicle 10 b and a fourth vehicle 10 c. Concurrently, or at least substantially overlapping in time, the second vehicle 10 a communicates with the first, third and fourth vehicles while the third vehicle 10 b communicates with the first, second and fourth vehicles and the fourth vehicle communicates with the first, second and third vehicles. The offers and acceptances may be conditional on the collateral offers and acceptances made with other vehicles at the intersection. The vehicles thus negotiate their respective traffic priorities automatically (without user intervention). The vehicles negotiate the amounts to be paid for the priorities and then complete the transactions.

FIG. 21 is an example of V2V messaging among four autonomous vehicles 10, 10 a, 10 b and 10 c at, or approaching, an intersection with traffic lights in which the vehicles are further configured to send signals that interact with the timing of the traffic lights. In this scenario, it is assumed that the traffic lights are intelligent traffic lights capable of receiving wireless signals from nearby vehicles and to adapt the timing of their lights in response to the signals from the vehicles. For example, an intelligent traffic light reacts to one or more requests from nearby vehicles to switch from a red light to a green light. Using V2V messaging, the autonomous vehicles automatically negotiate priorities for the vehicles at the intersection and then transfer payments to complete the transactions. Once the transactions are completed, the autonomous vehicles signal the intelligent traffic light to change. In another scenario, the traffic lights are conventional (as opposed to intelligent) traffic lights. The vehicles at or nearing the traffic lights can negotiate precedence to make a right turn on a red light with vehicles traveling on the crossing road onto which the red turn is being made.

FIG. 22 is an example of V2V messaging between two autonomous vehicles that are approaching a common parking place. In this example, the requesting vehicle 10 communicates via V2V messages 11 with the receiving vehicle 10 a to request precedence over the receiving vehicle in relation to the parking spot, i.e. to let the requesting vehicle take the last remaining parking spot. Detecting the parking spot may be done using a camera onboard the requesting vehicle or other means.

FIG. 23 is an example of V2V messaging amongst multiple autonomous vehicles that are approaching a parking lot with limited spaces available. In this example, four autonomous vehicles 10, 10 a, 10 b, 10 c exchange V2V messages 11 amongst each other to negotiate precedence (priority access) to the parking lot. The requesting vehicles transmit offers and receive acceptances, rejections or counteroffers from the receiving vehicles. The offers, acceptances, rejections and counteroffers are, in most embodiments, automatically generated and transmitted based on predetermined user settings, e.g. priority levels set by the user. The priority levels may be set based on time and/or location, e.g. per day, per hour, per route, per event type, for cities, neighbourhoods, points of interest, places, types of places, for user-defined areas or for any other definable locations. The priority levels may also have default settings that the user programs for the vehicle.

FIG. 24 is an example of a first autonomous vehicle 10 wirelessly tethered to a second autonomous vehicle 10 a and using the second autonomous vehicle 10 a as a wireless hotspot (or as a router or relay) in exchange for traffic reprioritization. In this example scenario, the second vehicle 10 a has already passed the first vehicle 10 and, in exchange for being allowed to pass, the second vehicle 10 a offers to the first vehicle 10 a wireless data connection to the second vehicle 10 a for the limited time when the two vehicles are within wireless range of each other. The download may be is limited in time and/or in data size and/or bandwidth. The first vehicle 10 may download digital content (music, movies, or other digital content) via the second vehicle's cellular or satellite connection. In the system shown in FIG. 24 , the digital content is downloaded from a digital content server 700 connected by a network device to the internet 250. The first vehicle can communicate with the server 700 by a cellular connection via the base stations transceiver 222 or by a satellite connection via a satellite 750 and ground station 760 connected to the internet 250.

FIG. 25 is an example of multiple users (e.g. a first set of passengers) riding a first autonomous bus 10 providing an aggregated request to multiple users (e.g. a second set of passengers) riding a second autonomous bus 10 a. In this case, the first set of passengers send individual requests via personal wireless communications device or mobile handheld devices (smart phones, cell phones, tablets, laptops, etc.) to a group request server 800 via a base station transceiver 222. The group request server is configured to sum, combine or aggregate these individual requests into a group request which is then conveyed to the second autonomous bus for broadcasting to the passengers or conveyed directly to the passengers on the second autonomous bus. The monetary value of the group request is divided equally and offered to each of the second set of passengers via their respective mobile devices. If the majority of the second set of passengers accept the offer, the first and second buses are reprioritized. In a variant, reprioritization of the buses occurs only by two-thirds majority or by another prescribed proportion. Alternatively, reprioritization can occur only if acceptance of the offer is unanimous. In another embodiment, the first bus may automatically negotiate with the second bus (without any intervention by the riders or passengers).

FIG. 26 is an example of a truck delivery system 900 in which three suppliers of goods automatically negotiate amongst each other, for example using algorithms, programmed rules or artificial intelligence, to determine automatic payments to be made amongst the suppliers to prioritize the access of their respective autonomous trucks (transport trucks, cargo vans, etc.) to a loading dock of a warehouse or store 910. In the system 900 depicted in FIG. 26 , a first factory/distributor/supplier 920 receives via a first supply management server 922 an order request from a stock management server 912 of the store 910 indicating that more goods are needed to replenish dwindling or empty stocks. The first supply management server 922 communicates automatically with a second supply management server 932 operated by a second factory/distributor/supplier 930 and optionally also with a third supply management server 942 operated by a third factory/distributor/supplier 940 to automatically negotiate reprioritization of first, second and third autonomous trucks 10, 10 a, 10 b en route to the store. In this example, the first truck 10 transports goods of the first factory/distributor/supplier 920, the second truck 10 a transports goods of the second factory/distributor/supplier 930, and the third truck 10 b transports goods of the third factory/distributor/supplier 940. The servers 922, 932, 942 of the three factory/distributor/suppliers 920, 930, 940 are configured to negotiate automatically amongst each other, using algorithms, rules and/or AI, a payment or payments to reprioritize the truck delivery times. Once a reprioritization transaction has been completed, the autonomous trucks 10, 10 a, 10 b are then signalled by the servers 922, 932 and 942 and reprioritized. Upon receipt of the signals, the trucks may perform their reprioritization manoeuvres or they may first communicate their intended actions to the other trucks and/or other vehicles in the vicinity prior to effecting the reprioritization action or manoeuvre.

FIG. 27 is an example of a ship delivery system 900 (analogous to the truck delivery system) in which three suppliers of goods, containers or other cargo automatically negotiate amongst each other, for example using algorithms, rules and/or artificial intelligence, to determine automatic payments to be made amongst the suppliers to prioritize the access of their respective autonomous ships to a dockside crane 915 or quayside berth in a harbour or port. In the example system of FIG. 27 , the first ship 10 transports goods of the first factory/distributor/supplier 920, the second ship 10 a transports goods of the second factory/distributor/supplier 930, and the third ship 10 b transports goods of the third factory/distributor/supplier 940. The respective servers 922, 932, 942 of the three factory/distributor/suppliers 920, 930, 940 are configured to negotiate automatically amongst each other via data messages through the internet 250 to pay to be granted priority access to the crane 915 or berth. Once the transaction is complete, the ships are notified by the servers and they are reprioritized accordingly.

FIG. 28 is an example of a drone delivery system 900 analogous to the truck delivery system and the ship delivery system in which three suppliers of goods (i.e. 920, 930, 940) automatically negotiate amongst each other, for example using algorithms, rules and/or artificial intelligence, to determine automatic payments to be made amongst the suppliers 920, 930, 940 to prioritize the access of their respective drones 10, 10 a, 10 b to a landing pad or other designated landing area. In one use case, the drones deliver goods to a store 910 having a landing pad. In another use case, the drones 10, 10 a, 10 b deliver goods to a house, residence, apartment building, condominium complex, gated community, resort, cottage, sports facility, restaurant, café or other business, etc. which has a landing pad or designated landing zone. In yet another use case, there is no designated landing pad or landing zone but the drones recognize that there is limited landing space and thus negotiate access to the limited landing space as if it were a landing pad or designated landing zone. Analogous to the preceding examples with the trucks and ships, the drone delivery system communicate reprioritization signals to the drones 10, 10 a, 10 b to cause them to stagger in time their arrivals at the store 910 or other delivery site. The drones that are delayed may hover nearby or be rerouted to make other deliveries, or may land nearby to await their turn. In another implementation, one drone that is granted precedence may provide a charge to another drone as a form of payment.

FIG. 29 is an example of user-configurable priority settings for different times of day that determine logic for how the vehicle automatically makes offers or accepts offers from other vehicles. In these exemplary settings, there are five levels of priority: very high, high, medium (normal), low and very low. Very high means that the user wishes to pay a significant amount to get prioritized treatment. High means that the user wishes to pay a modest amount to get prioritized treatment. Medium/normal means that the user does not wish to pay or be paid for any reprioritization. Low priority signifies that the user is willing to be paid a modest amount to give traffic priority to another vehicle. Very low priority signifies that the user requires to be paid a significant amount to give traffic priority to another vehicle. In the case of qualitative settings such as these, there would be a quantitative association table to indicate numerically what each priority level means in terms of pricing. In this example, the five timeslots are morning rush hour, evening rush hour, weekend daytime, weekend night time, and holidays. Other timeslots may be used. In one implementation, the timeslots may be user-defined by selecting from various menus of options to customize the timeslots that are most pertinent to the user.

FIG. 30 is an example of a user-configurable multipliers for setting prices for various types of traffic manoeuvres. In the example of FIG. 30 , the vehicle setting enables the user to specify a multiplier (in this case expressed as a percentage, either positive or negative) that is multiplied by the current price to determine what the vehicle is willing to offer or accept. A multiplier of +100% means that the vehicle is programmed to offer market price. A multiplier of −100% means the vehicle is programmed to accept market price. A multiplier of +150% means that the vehicle is programmed to make an offer (or accept a counteroffer) equal to 1.5 times the market price. A multiplier of −150% means that the vehicle is programmed to only accept an offer equal or greater to 1.5 times the market price. The market price may be determined by historical data for a given place and time. The user-configurable parameters are provided for different traffic manoeuvres or events. In this exemplary database, the traffic events are city passing, highway passing, prioritizing who goes first at a stop sign, prioritizing who gets a parking place, and merging into traffic (e.g. entering a highway from an onramp, changing lanes, etc.). These five are presented solely as an example. Fourteen time slots (for each day of the week both morning and afternoon) are presented in this example; however, it will be understood that this may be divided into any other suitable set of time slots, e.g. hourly.

The foregoing methods can be implemented in hardware, software, firmware or as any suitable combination thereof. That is, if implemented as software, the computer-readable medium comprises instructions in code which when loaded into memory and executed on a processor of a computing device causes the computing device to perform any of the foregoing method steps.

These method steps may be implemented as software, i.e. as coded instructions stored on a computer readable medium which performs the foregoing steps when the computer readable medium is loaded into memory and executed by the microprocessor of the computing device. A computer readable medium can be any means that contain, store, communicate, propagate or transport the program for use by or in connection with the instruction execution system, apparatus or device. The computer-readable medium may be electronic, magnetic, optical, electromagnetic, infrared or any semiconductor system or device. For example, computer executable code to perform the methods disclosed herein may be tangibly recorded on a computer-readable medium including, but not limited to, a floppy-disk, a CD-ROM, a DVD, RAM, ROM, EPROM, Flash Memory or any suitable memory card, etc. The method may also be implemented in hardware. A hardware implementation might employ discrete logic circuits having logic gates for implementing logic functions on data signals, an application-specific integrated circuit (ASIC) having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

For the purposes of interpreting this specification, when referring to elements of various embodiments of the present invention, the articles “a”, “an”, “the” and “said” are intended to mean that there are one or more of the elements. The terms “comprising”, “including”, “having”, “entailing” and “involving”, and verb tense variants thereof, are intended to be inclusive and open-ended by which it is meant that there may be additional elements other than the listed elements.

This new technology has been described in terms of specific implementations and configurations which are intended to be exemplary only. Persons of ordinary skill in the art will appreciate that many obvious variations, refinements and modifications may be made without departing from the inventive concepts presented in this application. The scope of the exclusive right sought by the Applicant(s) is therefore intended to be limited solely by the appended claims. 

The invention claimed is:
 1. A self-driving vehicle comprising: a vehicle chassis; a motor supported by the chassis for providing propulsive power for the vehicle; a braking system; a steering system; a plurality of sensors; a self-driving processor configured to receive signals from the sensors and to generate steering, acceleration and braking control signals for controlling the steering system, the motor and the braking system of the vehicle; a Global Navigation Satellite System (GNSS) receiver for receiving satellite signals and for determining a current location of the self-driving vehicle; a radiofrequency data transceiver; and a traffic-prioritization processor configured to cooperate with the radiofrequency data transceiver to: receive from a central server a price to obtain a traffic prioritization for a route or to accept a traffic de-prioritization for the route, wherein the central server determines the price based on offers and requests to be prioritized or deprioritized from other vehicles traveling the route and wherein the central server receives payments from prioritized vehicles traveling the route and distributes payments to de-prioritized vehicles traveling the route; and send or receive a payment to or from the central server to obtain the traffic prioritization for the route or to accept the traffic de-prioritization for the route.
 2. The self-driving vehicle of claim 1 wherein the traffic-prioritization processor is configured to cooperate with the radiofrequency data transceiver to receive, from the central server a plurality of levels of prioritization which range from a highest prioritization to a lowest prioritization, and the costs or payouts associated with each of the levels.
 3. The self-driving vehicle of claim 2 wherein the traffic-prioritization processor is configured to cooperate with the radiofrequency data transceiver to receive, from the central server, travel times for the levels of prioritization.
 4. The self-driving vehicle of claim 3 comprising a user interface to display the costs or payouts for the levels of prioritization and the travel times for each of the levels of prioritization to enable a user to select the level of prioritization for the route.
 5. The self-driving vehicle of claim 1 wherein the user interface provides an alert indicating that an estimated time of arrival at a destination will be later than originally predicted and providing a user interface element to enable a user to pay to expedite travel to the destination.
 6. The self-driving vehicle of claim 4 wherein the user interface displays the cost to pay to obtain the traffic prioritization to the destination.
 7. A self-driving vehicle comprising: a vehicle chassis; a motor supported by the chassis for providing propulsive power for the vehicle; a braking system; a steering system; a plurality of sensors; a self-driving processor configured to receive signals from the sensors and to generate steering, acceleration and braking control signals for controlling the steering system, the motor and the braking system of the vehicle; a Global Navigation Satellite System (GNSS) receiver for receiving satellite signals and for determining a current location of the self-driving vehicle; a radiofrequency data transceiver; and a traffic-prioritization processor that cooperates with the radiofrequency data transceiver to: receive, from a central server, pricing for different levels of traffic prioritization for a route, the pricing including a cost to obtain a higher traffic prioritization for the route and a payout to accept a lower traffic prioritization for the route.
 8. The self-driving vehicle of claim 7 wherein the traffic-prioritization processor is configured to cooperate with the radiofrequency data transceiver to send to the central server a payment equal to the cost of obtaining the higher traffic prioritization for the route.
 9. The self-driving vehicle of claim 7 wherein the traffic-prioritization processor is configured to cooperate with the radiofrequency data transceiver to receive from the central server a payment equal to the payout for accepting the lower traffic prioritization for the route.
 10. The self-driving vehicle of claim 7 further comprising a user interface presenting costs and payouts for three or more different levels of traffic prioritization.
 11. The self-driving vehicle of claim 10 wherein the user interface also presents costs and payouts based on times of day.
 12. The self-driving vehicle of claim 10 wherein the user interface also presents costs and payouts based on segments of the route.
 13. The self-driving vehicle of claim 10 wherein the user interface also presents travel times for the different levels of traffic prioritization.
 14. An autonomous vehicle comprising: a self-driving processor configured to receive signals from sensors to generate steering, acceleration and braking control signals for controlling a steering system, a motor and a braking system of the vehicle; a Global Navigation Satellite System (GNSS) receiver for receiving satellite signals and for determining a current location of the vehicle; a radiofrequency data transceiver; and a traffic-prioritization processor cooperating with the radiofrequency data transceiver to: communicate with a central server to receive pricing for a traffic prioritization or de-prioritization for a route; and send or receive a payment to or from the central server for the traffic prioritization or de-prioritization for the route.
 15. The autonomous vehicle of claim 14 wherein the pricing includes costs and payouts for different segments of the route.
 16. The autonomous vehicle of claim 15 wherein the costs and payouts for the different segments depend on a time of day.
 17. The autonomous vehicle of claim 14 comprising a user interface to present the costs and payouts to enable selection of a level of prioritization.
 18. The autonomous vehicle of claim 17 wherein the user interface indicates whether the costs and payouts are above normal market prices for that particular time and place.
 19. The autonomous vehicle of claim 14 wherein the pricing includes a bid and an ask for each segment of the route and for each level of prioritization, the bid defining a price being offered for the prioritization and the ask defining a price that is being asked to accept the prioritization.
 20. The autonomous vehicle of claim 14 wherein the self-driving processor and the traffic-prioritization processor are integrated in a vehicle computing device. 